by Kamauu, Aaron W. C.; DuVall, Scott L.; Avrin, David E.

Digital imaging and communication in medicine (DICOM) specifies that all DICOM objects have globally unique identifiers (UIDs). Creating these UIDs can be a difficult task due to the variety of techniques in use and the requirement to ensure global uniqueness. We present a simple technique of combining a root organization identifier, assigned descriptive identifiers, and JAVA generated unique identifiers to construct DICOM compliant UIDs.

DOI: 10.1007/s10278-007-9079-7
Online Date: 9/25/2007
Print publication date: 2/1/2009
View article on SpringerLink

by Sharma, Ashish; Pan, Tony; Cambazoglu, B. Barla; Gurcan, Metin; Kurc, Tahsin; Saltz, Joel

Collaborations in biomedical research and clinical studies require that data, software, and computational resources be shared between geographically distant institutions. In radiology, there is a related issue of sharing remote DICOM data over the Internet. This paper focuses on the problem of federating multiple image data resources such that clients can interact with them as if they are stored in a centralized PACS. We present a toolkit, called VirtualPACS, to support this functionality. Using the toolkit, users can perform standard DICOM operations (query, retrieve, and submit) across distributed image databases. The key features of the toolkit are: (1) VirtualPACS makes it easy to use existing DICOM client applications for data access; (2) it can easily be incorporated into an imaging workflow as a DICOM source; (3) using VirtualPACS, heterogeneous collections of DICOM sources are exposed to clients through a uniform interface and common data model; and (4) DICOM image databases without DICOM messaging can be accessed.

DOI: 10.1007/s10278-007-9074-z
Online Date: 9/18/2007
Print publication date: 2/1/2009
View article on SpringerLink

by Wang, Xiao Hui; Durick, Janet E.; Lu, Amy; Herbert, David L.; Golla, Saraswathi K.; Foley, Kristin; Piracha, C. Samia; Shinde, Dilip D.; Shindel, Betty E.; Fuhrman, Carl R.; Britton, Cynthia A.; Strollo, Diane C.; Shang, Sherry S.; Lacomis, Joan M.; Good, Walter F.

The goal of this study was to assess whether radiologists’ search paths for lung nodule detection in chest computed tomography (CT) between different rendering and display schemes have reliable properties that can be exploited as an indicator of ergonomic efficiency for the purpose of comparing different display paradigms. Eight radiologists retrospectively viewed 30 lung cancer screening CT exams, containing a total of 91 nodules, in each of three display modes [i.e., slice-by-slice, orthogonal maximum intensity projection (MIP) and stereoscopic] for the purpose of detecting and classifying lung nodules. Radiologists’ search patterns in the axial direction were recorded and analyzed along with the location, size, and shape for each detected feature, and the likelihood that the feature is an actual nodule. Nodule detection performance was analyzed by employing free-response receiver operating characteristic methods. Search paths were clearly different between slice-by-slice displays and volumetric displays but, aside from training and novelty effects, not between MIP and stereographic displays. Novelty and training effects were associated with the stereographic display mode, as evidenced by differences between the beginning and end of the study. The stereo display provided higher detection and classification performance with less interpretation time compared to other display modes tested in the study; however, the differences were not statistically significant. Our preliminary results indicate a potential role for the use of radiologists’ search paths in evaluating the relative ergonomic efficiencies of different display paradigms, but systematic training and practice is necessary to eliminate training curve and novelty effects before search strategies can be meaningfully compared.

DOI: 10.1007/s10278-007-9076-x
Online Date: 9/15/2007
Print publication date: 10/1/2008
View article on SpringerLink

by Rubin, Daniel L.

The radiology community has recognized the need to create a standard terminology to improve the clarity of reports, to reduce radiologist variation, to enable access to imaging information, and to improve the quality of practice. This need has recently led to the development of RadLex, a controlled terminology for radiology. The creation of RadLex has proved challenging in several respects: It has been difficult for users to peruse the large RadLex taxonomies and for curators to navigate the complex terminology structure to check it for errors and omissions. In this work, we demonstrate that the RadLex terminology can be translated into an ontology, a representation of terminologies that is both human-browsable and machine-processable. We also show that creating this ontology permits computational analysis of RadLex and enables its use in a variety of computer applications. We believe that adopting an ontology representation of RadLex will permit more widespread use of the terminology and make it easier to collect feedback from the community that will ultimately lead to improving RadLex.

DOI: 10.1007/s10278-007-9073-0
Online Date: 9/15/2007
Print publication date: 12/1/2008
View article on SpringerLink

by Sanchez Jacob, R.; Vano-Galvan, E.; Vano, E.; Gomez Ruiz, N.; Fernandez Soto, J. M.; Martinez Barrio, D.; Prieto, C.

The objective of this study was to analyze image quality of chest examinations in pediatric patients using computed radiography (CR) obtained with a wide range of doses to suggest the appropriate parameters for optimal image quality. A sample of 240 chest images in four age ranges was randomly selected from the examinations performed during 2004. Images were obtained using a CR system and were evaluated independently by three radiologists. Each image was scored using criteria proposed by the European Guidelines on Quality Criteria in Pediatrics. Mean global scoring and scoring of individual criteria more sensitive to noise were used to evaluate image quality. Agfa dose level (DL) was in the range 1.20 to 2.85. It was found that there was not significant correlation (R < 0.5) between image quality and DL for any of the age ranges for either global score or for individual criteria more related to noise. The mean value of DL was in the ranges 1.9–2.1 for the four age bands. From this study, a DL value of 1.6 is proposed for pediatric CR chest imaging. This could yield a reduction of approximately a factor of 2.5 in mean patient entrance surface doses.

DOI: 10.1007/s10278-007-9071-2
Online Date: 9/13/2007
Print publication date: 4/1/2009
View article on SpringerLink

by Mueen, A.; Zainuddin, R.; Baba, M. Sapiyan

Image retrieval at the semantic level mostly depends on image annotation or image classification. Image annotation performance largely depends on three issues: (1) automatic image feature extraction; (2) a semantic image concept modeling; (3) algorithm for semantic image annotation. To address first issue, multilevel features are extracted to construct the feature vector, which represents the contents of the image. To address second issue, domain-dependent concept hierarchy is constructed for interpretation of image semantic concepts. To address third issue, automatic multilevel code generation is proposed for image classification and multilevel image annotation. We make use of the existing image annotation to address second and third issues. Our experiments on a specific domain of X-ray images have given encouraging results.

DOI: 10.1007/s10278-007-9070-3
Online Date: 9/11/2007
Print publication date: 9/1/2008
View article on SpringerLink

by Nascimento, Marcelo Zanchetta; Frère, Annie France; Germano, Fernao

The most significant radiation field nonuniformity is the well-known Heel effect. This nonuniform beam effect has a negative influence on the results of computer-aided diagnosis of mammograms, which is frequently used for early cancer detection. This paper presents a method to correct all pixels in the mammography image according to the excess or lack on radiation to which these have been submitted as a result of the this effect. The current simulation method calculates the intensities at all points of the image plane. In the simulated image, the percentage of radiation received by all the points takes the center of the field as reference. In the digitized mammography, the percentages of the optical density of all the pixels of the analyzed image are also calculated. The Heel effect causes a Gaussian distribution around the anode–cathode axis and a logarithmic distribution parallel to this axis. Those characteristic distributions are used to determine the center of the radiation field as well as the cathode–anode axis, allowing for the automatic determination of the correlation between these two sets of data. The measurements obtained with our proposed method differs on average by 2.49 mm in the direction perpendicular to the anode–cathode axis and 2.02 mm parallel to the anode–cathode axis of commercial equipment. The method eliminates around 94% of the Heel effect in the radiological image and the objects will reflect their x-ray absorption. To evaluate this method, experimental data was taken from known objects, but could also be done with clinical and digital images.

DOI: 10.1007/s10278-007-9072-1
Online Date: 9/11/2007
Print publication date: 6/1/2008
View article on SpringerLink

by Kim, Kwang-Baek; Kim, Chang Won; Kim, Gwang Ha

In Korea, hepatocellular carcinoma is the third frequent cause of cancer death, occupying 17.2% among the whole deaths from cancer, and the rate of death from hepatocellular carcinoma comes to about 21 out of 100,000. This paper proposes an automatic method for the extraction of areas being suspicious as hepatocellular carcinoma from computed tomography (CT) scans and evaluates the availability as an auxiliary tool for the diagnosis of hepatocellular carcinoma. For detecting tumors in the internal of the liver from a CT scan, first, an area of the liver is extracted from about 45–50 CT slices obtained by scanning in 2.5-mm intervals starting from the lower part of the chest. In the extraction of an area of the liver, after the unconcerned areas outside of the bony thorax are removed, areas of the internal organs are segmented by using information on the intensity distribution of each organ, and an area of the liver is extracted among the segmented areas by using information on the position and morphology of the liver. Because hepatocellular carcinoma is a hypervascular tumor, the area corresponding to hepatocellular carcinoma appears more brightly than the surroundings in a CT scan, and also takes a spherical shape if the tumor shows expansile growth pattern. By using these features, areas being brighter than the surroundings and globe-shaped are segmented as candidate areas for hepatocellular carcinoma in the area of the liver, and then, areas appearing at the same position in successive CT slices among the candidates are discriminated as hepatocellular carcinoma. For the performance evaluation of the proposed method, experimental results obtained by applying the proposed method to CT scans were compared with the diagnoses by radiologists. The evaluation results showed that all areas of the liver and hypervascular tumors were extracted exactly and the proposed method has a high availability as an auxiliary diagnosis tool for the discrimination of liver tumors.

DOI: 10.1007/s10278-007-9053-4
Online Date: 9/6/2007
Print publication date: 10/1/2008
View article on SpringerLink

by Lee, Kyoung Ho; Hong, Helen; Hahn, Seokyung; Kim, Bohyoung; Kim, Kil Joong; Kim, Young Hoon

We hypothesized that that the summation or axial slab average intensity projection (AIP) techniques can substitute for the primary reconstruction (PR) from a raw projection data for abdominal applications. To compare with PR datasets (5-mm thick, 20% overlap) in 150 abdominal studies, corresponding summation and AIP datasets were calculated from 2-mm thick images (50% overlap). The root-mean-square error between PR and summation images was significantly greater than that between PR and AIP images (9.55 [median] vs. 7.12, p < 0.0001, Wilcoxon signed-ranks test). Four radiologists independently compared 2,000 test images (PR [as control], summation, or AIP) and their corresponding PR images to prove that the identicalness of summation or AIP images to PR images was not 1% less than the assessed identicalness of PR images to themselves (Wald-type test for clustered matched-pair data in a non-inferiority design). For each reader, both summation and AIP images were not inferior to PR images in terms of being rated identical to PR (p < 0.05). Although summation and AIP techniques produce images that differ from PR images, these differences are not easily perceived by radiologists. Thus, the summation or AIP techniques can substitute for PR for the primary interpretation of abdominal CT.

DOI: 10.1007/s10278-007-9067-y
Online Date: 9/6/2007
Print publication date: 12/1/2008
View article on SpringerLink

by Kamauu, Aaron W. C.; DuVall, Scott L.; Liimatta, Andrew P.; Wiggins, Richard H.; Avrin, David E.

The Integrating the Healthcare Enterprise (IHE) Teaching File and Clinical Trial Export (TCE) integration profile describes a standard workflow for exporting key images from an image manager/archive to a teaching file, clinical trial, or electronic publication application. Two specific digital imaging and communication in medicine (DICOM) structured reports (SR) reference the key images and contain associated case information. This paper presents step-by-step instructions for translating the TCE document templates into functional and complete DICOM SR objects. Others will benefit from these instructions in developing TCE compliant applications.

DOI: 10.1007/s10278-007-9052-5
Online Date: 9/4/2007
Print publication date: 12/1/2008
View article on SpringerLink